Business
Product-Market Fit Generator
A product-market fit assessment generator builds a structured diagnostic centred on the Sean Ellis test. Enter your product name and it returns the canonical survey question — how users would feel if they could no longer use it — with the 40% "very disappointed" benchmark, plus prompts to identify your most loyal segment, the benefit they cite, your retention curve shape, organic growth signals, and a verdict of pre-fit, approaching, or fit. Founders and product managers use this before pouring budget into growth, because scaling a pre-fit product amplifies the problem. PMF is felt as pull — demand outstrips capacity and retention curves plateau rather than decay. Run the survey with real active users, study who answers "very disappointed," and use that segment to sharpen the product.
How to use
- Choose your options above
- Click Generate
- Copy your result
Detailed instructions
- Enter your product.
- Click Generate to produce the assessment.
- Run the survey with real, active users.
- Study the "very disappointed" segment and iterate.
Use Cases
- •Assessing product-market fit with evidence, not gut feel
- •Running the Sean Ellis 40% PMF survey
- •Identifying the segment that loves the product most
- •Reading a retention curve for signs of fit
- •Deciding whether it is time to scale or keep iterating
Tips
- →Aim for the 40% "very disappointed" benchmark.
- →Double down on the segment that loves it most.
- →Look for a flattening retention curve, not just growth.
- →Treat real pull, not push, as the sign of fit.
FAQ
What is the Sean Ellis test?
You ask users how they would feel if they could no longer use your product. If at least 40% say "very disappointed," that strongly signals product-market fit. Below that threshold, focus on the loyal segment and the benefit they cite to understand what to improve.
How does the retention curve indicate product-market fit?
Plot the share of users still active over time. With fit, the curve flattens into a stable plateau — a core group keeps coming back. Without fit, it decays toward zero. A flattening curve is one of the clearest, most objective fit signals available.
Why focus on the "very disappointed" users specifically?
They are your true market. Studying who they are and what benefit they would miss most tells you who to serve and how to sharpen the product. Widening from that loyal core beats trying to please everyone before you have fit.
What are signs you do NOT have product-market fit?
Usage decaying to zero instead of plateauing, growth that stalls the moment ad spend stops, weak word of mouth, and well under 40% of users saying they would be very disappointed without you. Sales feels like pushing, not pulling.
Can you lose product-market fit after reaching it?
Yes — markets shift, competitors catch up, and customer needs evolve, so fit is a state you maintain, not a finish line. Rerun the assessment periodically and track the "very disappointed" percentage over time so you notice fit eroding while there is still time to respond.
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